Non-invasive screening for coronary artery disease in asymptomatic diabetic patients: a systematic review and meta-analysis of randomised controlled trials

Non-invasive screening for coronary artery disease in asymptomatic diabetic patients: a... Abstract It is unclear whether non-invasive screening of asymptomatic diabetic patients for coronary artery disease (CAD) may improve cardiac outcomes. Thus, we performed a systematic literature review and meta-analysis of randomised controlled trials (RCT’s) on this topic. We searched appropriate RCT’s in five online databases (PubMed/MEDLINE, Cochrane Library, Embase, Scopus, and Web of Science) from January 2000 to November 2017 and in 41 recent reviews. Two investigators independently extracted and assessed study data using standardised forms. Additional unpublished data were obtained from trial authors. The primary endpoint ‘any cardiac event’ was a composite of cardiac death, non-fatal myocardial infarction (MI), unstable angina (UA), or heart failure (HF) hospitalisation. We performed a meta-analysis of relative risks (RRs) with 95% confidence intervals (CI) using the Mantel–Haenszel method. We included five RCT’s with 3299 patients, of which 189 (5.7%) experienced any cardiac event on follow-up (weighted mean 4.1 years). Non-invasive CAD screening significantly reduced any cardiac event by 27% [RR 0.73 (95% CI 0.55–0.97), P = 0.028, number needed to screen 56]. This result was driven by important, albeit non-significant decreases in non-fatal MI [RR 0.65 (95% CI 0.41–1.02), P = 0.062] and HF hospitalisation [RR 0.61 (95% CI 0.33–1.10), P = 0.100]. Non-invasive CAD screening did not significantly affect cardiac death [RR 0.92 (95% CI 0.53–1.60), P = 0.77] and UA [RR 0.73 (95% CI 0.41–1.31), P = 0.29]. Compared with the standard care, non-invasive CAD screening reduced cardiac events by 27% in asymptomatic diabetic patients, largely through reductions in non-fatal MIs, and HF hospitalisations. The present results justify larger, appropriately powered trials to potentially revisit current recommendations. meta-analysis, screening, stress testing, cardiac imaging, coronary artery disease, diabetes mellitus Introduction Globally, an estimated 422 million people are living with diabetes mellitus, a number that has doubled over the past 20–30 years.1 By 2045, the International Diabetes Federation expects a further increase to 629 million diabetic patients worldwide.2 Diabetes mellitus confers a two-fold increased risk of coronary artery disease (CAD),3 which is the major cause of mortality and morbidity in diabetic patients.4–6 Unfortunately, in these patients, CAD may often be asymptomatic until the onset of myocardial infarction (MI) or sudden cardiac death.4,5,7 Indeed, silent cardiac ischaemia can be detected on average in 26% of asymptomatic diabetic patents, exposing them to a 3.5-fold increased risk of cardiac events.8 Hence, diabetes mellitus has been considered a CAD risk equivalent.9 The current standards of care for asymptomatic diabetic patients are based on risk factor modification, lifestyle changes, and medical therapy.6,10 However, the high cardiovascular risk in these patients has also generated substantial interest in the early detection of silent CAD by screening tests.5 In addition to exercise electrocardiogram test (EET), recent technological advances have produced a number of sophisticated imaging tools to assess non-invasively the presence and severity of CAD, including stress echocardiography (SE), stress radionuclide myocardial perfusion imaging (MPI), coronary artery calcium scoring (CACS), and computed tomography coronary angiography (CTCA).11 Myocardial ischaemia, high CACS and significant coronary stenosis have all been associated with worse outcomes in non-diabetic12,13 and diabetic patients.8,11,14,15 However, whether pre-emptive coronary revascularization and intensification of medical therapy based on routine CAD screening may improve outcomes of asymptomatic diabetic patients is currently under debate.16,17 Experts favouring screening5,16 refer to the improvement of risk classification,18 and the reduction of scintigraphic CAD progression with invasive treatment.19 However, opponents advocate optimal medical treatment without screening because revascularization has not convincingly been demonstrated to reduce cardiovascular events in diabetic patients.20,21 Moreover, first exploratory randomised controlled trials (RCT’s) failed to demonstrate any prognostic benefit of CAD screening. However, these trials may have suffered from under-sampling and potential statistical Type II error due to lower event rates than anticipated.22,23 We, therefore, sought to perform a systematic review and meta-analysis of published RCT’s to assess more precisely and with higher statistical power the potential reduction of cardiac events by a systematic non-invasive CAD screening strategy in asymptomatic patients with diabetes mellitus. Methods Literature search We performed a systematic search of medical articles published in peer-reviewed journals from January 2000 to November 2017 in English, German, or French in five online literature databases (PubMed/MEDLINE, Cochrane Library, Embase, Scopus, and Web of Science) using the following words in titles, abstracts, or keywords: (‘diabetes’ or ‘diabetic’), (‘asymptomatic’ or ‘occult’ or ‘silent’ or ‘subclinical’ or ‘unknown’), (‘coronary’ or ‘ischemia’ or ‘ischaemia’ or ‘CAD’), and (‘screening’ or ‘detection’ or ‘diagnosis’ or ‘identification’). Additionally, we manually searched the bibliographies of relevant reviews and guidelines of the last 10 years. Study selection We selected publications according to the following criteria: (i) prospective RCT’s published in peer-reviewed journals, (ii) patients with diabetes mellitus, without CAD symptoms or known CAD, (iii) randomisation to a non-invasive CAD screening strategy vs. standard care arm, and (iv) comparison of cardiac events after ≥1 year of follow-up, analysed with the intention-to-treat principle. Non-RCT’s with an adequate control group and meeting all other criteria were included in additional analyses. An overview of the search protocol is presented in Figure 1. Figure 1 View largeDownload slide Study flow diagram. Figure 1 View largeDownload slide Study flow diagram. Outcomes Our primary endpoint ‘any cardiac event’ was a composite of cardiac death, non-fatal MI, unstable angina (UA), or heart failure (HF) hospitalisation. Secondary endpoints were the individual components of the primary endpoint, all-cause death, coronary revascularization (regardless of percutaneous vs. surgical, as part of the screening protocol or not), and medication use. Data extraction Two investigators (O.F.C. and O.G.) independently extracted data regarding trial characteristics, potential bias, and pre-specified cardiac outcomes from the selected RCT’s using standardised forms designed for this study. Differences were solved by consensus. Composite outcome data were patient-based (i.e. one patient with several events counted as one positive case). For one study,24 we re-included one patient excluded for early non-cardiac death. Moreover, we contacted the authors of all selected trials to complete our outcome data. Thus, we were able to include unpublished results in our analyses. Study quality and risk of bias The study quality assessment comprised the risk of study bias, the publication bias, and the overall quality of evidence. The risk of study bias was assessed at the study and outcome level using the Cochrane Collaboration’s tool.25 Publication bias was evaluated using funnel plots26 and the Harbord–Egger test for asymmetry.27,28 Finally, overall quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method29 updated by the Evidence-based Practice Centre.30 Data synthesis and analysis Statistical analyses were conducted with Review Manager (RevMan) Version 5.3.5 (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). Additional graphics were generated with MedCalc version 17.4 (MedCalc Software bvba, Ostend, Belgium, 2017) and the Harbord–Egger test was performed with StatsDirect version 3.0.199 (StatsDirect Ltd., UK, 2013). Heterogeneity of trial results was tested using Cochrane’s Q and I2 statistic.31 We performed a meta-analysis of relative risks (RRs) with 95% confidence intervals (CIs) using the Mantel–Haenszel method and the fixed effect model.32 A random effects model33 was used if heterogeneity was significant (P ≤ 0.10 or I2 ≥ 50%)31 and in all additional analyses including non-RCT’s. The number needed to screen (NNS) was calculated for outcomes with significant results. All statistical tests were two-sided, and P-values <0.05 were considered as statistically significant, except <0.10 for heterogeneity analyses, as recommended.31 Sensitivity analyses For all primary and secondary endpoints, we sequentially excluded each trial from the meta-analysis to assess its specific effect on the pooled RR and significance. Additional analyses including non-randomised trials All primary and secondary endpoints were re-analysed after including data from the selected non-RCT’s. Regulatory aspects Because our study did not directly involve patients, but only outcome data from other studies, no approval from the local ethics committee was required. However, all selected trials reported about approval by an institutional review board and informed consent by each patient. Our analysis complied with the Declaration of Helsinki. We presented our results according to the PRISMA statement about systematic reviews and meta-analyses.34 This study did not receive any funding. Results Literature search Our literature search covered five online databases (5392 total records), and was completed using 35 reviews (1737 references) and six guidelines (1760 references), with substantial overlap of citations (Figure 1). We identified the five following appropriate RCT’s: the study by Faglia et al.,24 the ‘Detection of Ischaemia in Asymptomatic Diabetics’ (DIAD) study,22 the ‘Do You Need to Assess Myocardial Ischaemia in Type-2 diabetes’ (DYNAMIT) study,35 the FACTOR-64 study,23 and the ‘Does coronary Atherosclerosis Deserve to be Diagnosed earlY in Diabetic patients’ (DADDY-D) study.36 Study characteristics Table 1 presents important characteristics of the selected RCT’s. These trials included between 141 and 1123 patients, with a total of 3299 patients. Mean age ranged from 60.1 to 63.9 years, the proportion of male patients from 52% to 80% and mean follow-up duration from 3.5 to 4.8 years (weighted mean 4.1 years). Inclusion criteria were based on age and presence of diabetes, and three studies required additional cardiovascular risk factors. Screening was performed with EET, SE, MPI, CTCA with CACS, or a combination of them. The studies also vary in the type of clinical response with which pathological imaging findings were met: in DIAD, patients were treated according to the best judgment of the primary medical provider. In DYNAMIT, further investigations were left at the cardiologist’s decision. In Faglia et al.24 and DADDY-D, patients with positive tests were directly offered an invasive coronary angiography (ICA). FACTOR-64 provided protocol-based recommendations to the referring physicians on intensification of medical treatment and the use of ICA or further non-invasive testing based on the severity of findings. All selected RCT’s consistently found non-significant reductions of cardiac events in the screening arm, except Faglia et al.24 showing significant reductions of major and all cardiac events. Table 1 Overview of the randomised controlled trials included in the meta-analysis Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old CACS, coronary artery calcium score; CAD, coronary artery disease; CE, cardiac events (major CE = cardiac death or MI); CTCA, computed tomography coronary angiography; CV, cardiovascular; CVRF, cardiovascular risk factors; DM, diabetes mellitus; EET, exercise electrocardiogram test; ICA, invasive coronary angiography; MI, myocardial infarction; MPI, radionuclide myocardial perfusion imaging; SE, stress echocardiography. a In Faglia et al.,24 we re-included one patient excluded for early non-cardiac death. Table 1 Overview of the randomised controlled trials included in the meta-analysis Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old CACS, coronary artery calcium score; CAD, coronary artery disease; CE, cardiac events (major CE = cardiac death or MI); CTCA, computed tomography coronary angiography; CV, cardiovascular; CVRF, cardiovascular risk factors; DM, diabetes mellitus; EET, exercise electrocardiogram test; ICA, invasive coronary angiography; MI, myocardial infarction; MPI, radionuclide myocardial perfusion imaging; SE, stress echocardiography. a In Faglia et al.,24 we re-included one patient excluded for early non-cardiac death. Study quality and risk of bias The five RCT’s had a globally low risk of study bias when assessed with the Cochrane tool (see Supplementary data online, Figure S1). Importantly, all of them seemed non-blinded to patients and physicians regarding trial arm. However, knowledge of screening status and screening results was an integral part of the interventions and thus, we did not consider it as a bias. Two studies had a comparable number of patients lost to follow-up and of patients experiencing cardiac events, leading to a potential minor attrition bias. Trial results were direct, as they were based on clinical outcomes. Consistency of results was good for most of these outcomes. Regarding publication bias, funnel plots showed a somewhat outlying position for Faglia et al.,24 consistent with its small size and more positive results (see Supplementary data online, Figure S2). However, we found no significant asymmetry with the Harbord–Egger test (P = 0.123 for the main composite outcome). Finally, the individual trials lacked precision, due to broad CIs, but performing a meta-analysis produced more precise results. However, these analyses are limited in the presence of five RCT’s. Thus, we rated the strength of evidence as moderate, according to the updated GRADE method. Primary outcome and its components In our sample of five RCT’s, a total of 3299 patients were randomised to a screening arm (n = 1652) or a control arm (n = 1647). A total of 189 (5.7%) patients experienced cardiac events. A strategy of non-invasive CAD screening significantly reduced any cardiac event by 27% [RR 0.73 (95% CI 0.55–0.97), P = 0.028, I2 = 36%, NNS = 56, Figure 2]. This was largely driven by a decrease in non-fatal MI [RR 0.65 (95% CI 0.41–1.02), P = 0.062, I2 = 0%] and HF hospitalisation [RR 0.61 (95% CI 0.33–1.10), P = 0.100, I2 = 29%], although both findings fell short of statistical significance when assessed separately (Figure 3). Screening tended to reduce UA [RR 0.73 (95% CI 0.41–1.31), P = 0.29, I2 = 0%], but had no relevant effect on cardiac death [RR 0.92 (95% CI 0.53–1.60), P = 0.77, I2 = 39%, Figure 3]. Figure 2 View largeDownload slide Meta-analysis of the primary endpoint: any cardiac event. Any cardiac event is a composite of cardiac death, non-fatal myocardial infarction, unstable angina, or heart failure hospitalisation. Figure 2 View largeDownload slide Meta-analysis of the primary endpoint: any cardiac event. Any cardiac event is a composite of cardiac death, non-fatal myocardial infarction, unstable angina, or heart failure hospitalisation. Figure 3 View largeDownload slide Meta-analysis of components of the primary endpoint. Figure 3 View largeDownload slide Meta-analysis of components of the primary endpoint. Secondary outcomes All-cause death was not affected by screening [RR 0.92 (95% CI 0.65–1.30), P = 0.63, I2 = 0%, Figure 4]. Coronary revascularization was heterogeneous across the RCT’s (I2 = 79%). Whereas trials with functional testing (EET and MPI) tended to decrease revascularization rates, anatomical testing (CTCA + CACS in FACTOR-64) significantly increased it (Figure 4). Analyses of medication use showed no significant effect of screening, but detected a trend towards increased statin use [RR 1.05 (95% CI 0.99–1.10), P = 0.092, I2 = 31%, see Supplementary data online, Figure S3]. Figure 4 View largeDownload slide Meta-analysis of secondary endpoints. Figure 4 View largeDownload slide Meta-analysis of secondary endpoints. Sensitivity analysis In the primary endpoint analysis, excluding Faglia et al.24 or DADDY-D numerically increased the pooled RR, whereas excluding DIAD, DYNAMIT, or FACTOR-64 reduced it. Excluding Faglia et al. or DADDY-D made the pooled RR statistically non-significant, whereas excluding DIAD made it more significant. The most divergent results were: without Faglia et al. [RR 0.82 (95% CI 0.61–1.09), P = 0.172, I2 = 0%], without DIAD [RR 0.65 (95% CI 0.47–0.91), P = 0.013, I2 = 41%, NNS = 38]. Among secondary outcomes, screening would tend to reduce cardiac death without DYNAMIT [RR 0.70 (95% CI 0.37–1.30), P = 0.26, I2 = 16%] and to reduce coronary revascularizations without FACTOR-64 [RR 0.81 (95% CI 0.59–1.09), P = 0.159, I2 = 0%]. Additional analyses including non-randomised trials In the literature search, we found two relevant non-RCT’s with appropriate control groups, both showing reductions in cardiovascular events in screened asymptomatic patients with diabetes: one by Gazzaruso et al.37 using EET ± SE or MPI and one by Tsujimoto et al.38 using MPI. Including these non-RCT’s into the primary outcome analysis resulted in a stronger reduction of any cardiac event by 42% [RR 0.58 (95% CI 0.37–0.91), P = 0.017, I2 = 66%, NNS = 35, Figure 5], driven by a significant reduction of non-fatal MI [RR 0.52 (95% CI 0.32–0.84), P = 0.008, I2 = 31%]. Secondary endpoints including non-RCT’s are presented in Supplementary data online, Figure S4. Figure 5 View largeDownload slide Meta-analysis of any cardiac event in randomised controlled trials and non-randomised trials. Figure 5 View largeDownload slide Meta-analysis of any cardiac event in randomised controlled trials and non-randomised trials. Discussion The present meta-analysis of five RCT’s including 3299 asymptomatic diabetic patients compared a strategy of routine CAD screening vs. standard of care with regard to cardiac outcomes over a weighted mean follow-up of 4.1 years. We found a significant reduction in the primary composite endpoint of any cardiac event by 27%. This endpoint reduction was mainly driven by lower rates of non-fatal MI (−35%) and HF hospitalisations (−39%), although both findings fell short of statistical significance when assessed separately. Fifty-six asymptomatic Type 2 diabetics would have to undergo CAD screening to prevent one cardiac event over a 4-year follow-up. Overall quality of evidence was high. Including data from two non-randomised trials in the meta-analysis further strengthened the effect of screening on the primary endpoint (−42%) and even showed a significant reduction in non-fatal MI by 48% in favour of screening. This primary outcome reduction was fairly homogenous over the five trials included in the meta-analysis, but fell short of statistical significance when assessed separately in each individual trial (except in the small trial by Faglia et al.24). This may be explained by a Type II statistical error, in which the null hypothesis fails to be rejected due to systematic under-sampling, caused by the unexpected low cardiac event rates in all trials. Indeed, in DIAD and FACTOR-64, the two largest RCT’s included in this meta-analysis, the average annual major cardiac event rate (cardiac death or MI) was 0.6%, and 0.8%, respectively, i.e. 3–4 times lower than anticipated.22,23 Unlike the other RCT’s, all of which had higher event rates, DIAD and FACTOR-64 did not require additional risk factors as inclusion criteria. Hence, it is likely that both trials were underpowered to detect small differences in risk at a reasonable power (80–90%). Most of the studies encountered difficulties in enrolling patients: DYNAMIT was stopped early due to low patient recruitment rates,35 whereas FACTOR-64 and DADDY-D compensated low recruitment rates by extending the follow-up duration.23,36 The present meta-analysis overcomes the statistical limitations of the individual trials to some extent and confirms the small but significant tendency towards improved outcomes with the use of a CAD screening strategy. Notably, pathological screening results were treated differently across the different trials. In DIAD and DYNAMIT, specific treatment decisions regarding intensification of medical treatment and/or referral to ICA were left at the discretion of the treating physician or the study cardiologist.22,35 In Faglia et al.24 and DADDY-D,36 patients with pathological test results were directly offered an ICA. Only FACTOR-64 provided standardised protocol-based recommendations for treatment escalation in the screening arm: these included lower-than-standard goals for cholesterol, HbA1c, and blood pressure. Patients with severe or moderate coronary stenoses on CTCA were sent for ICA or further non-invasive testing, respectively. However, despite more aggressive treatment in 70% of patients in the screening arm of FACTOR-64, differences in lipid levels, blood pressure, and HbA1c between both groups were very modest after treatment. Coronary angiography and revascularization rates were slightly higher in the screening arm compared with the standard-of-care arm. Possibly as a result of this, a small non-significant trend towards improved outcomes was observed in the screening arm.23 In DIAD, there were no significant differences with regard to medical treatment and the rate of revascularization between both groups. In fact, only 15% of patients with moderate to large perfusion defects underwent ICA, and numerically more patients with normal imaging findings than patients with perfusion defects were revascularized. Almost 80% of patients with moderate to large perfusion defects, and 96% of patients with small perfusion defects were denied a revascularization procedure. Thus, presumably those patients with the largest expected benefit from revascularization were withheld.12 These discrepancies between individual and recommended treatment decisions may account to some extent for the lack of benefit in the screening arm of DIAD.22 In DYNAMIT and DADDY-D, drug usage and revascularization rates were similar among both groups, but severity of ischaemia and respective revascularization rates are not reported.35,36 Current recommendations for CAD screening in asymptomatic diabetic patients are rather restrictive, based on the negative results of the aforementioned screening trials. Multimodality appropriate use criteria for CAD detection consider EET as ‘appropriate’ and imaging tests as ‘maybe appropriate’ in asymptomatic diabetic patients.39 European and American cardiological societies do not recommend systematic screening of asymptomatic diabetic patients, but consider CACS as reasonable and mention that stress imaging may be considered.40,41 However, the American Diabetes Association clearly discourages routine CAD screening on the following grounds6: on one hand, diabetic patients should already be on aggressive primary prevention therapies regardless of the presence or absence of significant CAD, on the other hand, large randomised trials did not report any global advantage of revascularization over medical therapy in unselected Type 2 diabetic patients with stable CAD.20,21 The present meta-analysis argues against current recommendations and encourages further research into screening strategies for asymptomatic diabetic patients. Given the large global prevalence of diabetes mellitus and the considerable costs of current non-invasive CAD imaging tests, it would be premature to recommend routine CAD screening for every asymptomatic diabetic patient. Moreover, the present meta-analysis did not demonstrate any mortality benefit with a screening strategy. However, the benefit of a screening strategy in this study can be compared with the effect of statin use for primary prevention of coronary heart disease events (−27%, number needed to treat 78).42 Further large and appropriately powered trials are required to allow a more precise analysis of the magnitude of benefit and to assess pre-specified subgroups in which screening strategies may offer larger benefits. Then, cost-effectiveness studies should assess the financial impact and economic benefits of a CAD screening programme in diabetic patients. Limitations This meta-analysis was based on a variety of screening modalities: FACTOR-64 used CACS and CTCA,23 while DIAD was conducted with MPI,22 DYNAMIT and DADDY-D relied on EET,35,36 whereas Faglia et al.24 combined EET and SE. These methodological differences may be perceived as a limitation of our meta-analysis. However, with the exception of EET, all CAD imaging tests have demonstrated uniformly a very high sensitivity and specificity for detecting CAD.40 Moreover, all non-invasive tests predict cardiac events based on the severity of their findings, also in patients with diabetes.8,11,14,15 Furthermore, the extent of disease has been shown to interact with the treatment strategy with regard to cardiac outcomes. Thus, patients with more severe or extensive CAD on non-invasive testing have better outcomes with revascularization, while in patients with lower CAD severity, medical therapy appears equivalent.12,43 The design of this study-level meta-analysis precludes assessing specific subgroups for their respective benefits of screening strategies. Given the small prognostic benefit of a routine screening strategy, it may well be that larger benefits are observed in specific subgroups, such as the very high-risk diabetic patients (e.g. those in which medical therapy fails to reach therapeutic goals or with multiple risk factors), the elder diabetics (as suggested in DADDY-D36), or those with a high level of physical activity. Moreover, only FACTOR-64 included 12% of patients with Type 1 diabetes.23 This corresponds to 3% of our pooled sample, with 97% of patients having Type 2 diabetes. Thus, our results essentially apply to Type 2 diabetes. However, our meta-analysis also has strengths, such as the low risk of bias of the selected RCT’s, the overall quality of evidence, the detailed outcome assessment, the addition of unpublished data, and the additional analyses with non-randomised trials. Conclusion The present systematic review and meta-analysis suggests a reduction of cardiac events with the use of a CAD screening strategy in asymptomatic diabetic patients. These results should encourage further research into this issue by design of larger, appropriately sized randomised trials to address the exact magnitude of the effect in specific subgroups. Acknowledgements We thank the trial authors for providing additional information and unpublished data: Dr C. Gazzaruso, Prof M. Noda, Dr T. Tsujimoto, Dr F. Turrini, Dr M. Lièvre, Dr J.B. Muhlestein, and Dr S. Knight. Supplementary data Supplementary data are available at European Heart Journal - Cardiovascular Imaging online. Conflict of interest: None declared for this study. In the original trials, Faglia et al. did not report about conflicts of interests or financial support. DIAD was supported by Bristol Myers-Squibb Medical Imaging and Astellas Pharma, which provided technetium-99m-sestamibi and adenosine. DYNAMIT was supported by the French Social Security, ALFEDIAM, Aventis, Pfizer-Parke-Davis, and Servier. FACTOR-64 was supported by Toshiba Corporation and Bracco Corporation. DADDY-D reported no conflict of interest and no private funding, but additional study materials from Azienda USL di Modena. Gazzaruso et al. reported no conflict of interest. Tsujimoto et al. were supported by the Japan Diabetes Foundation, and reported speaker honoraria and grants for the last author. All industry-supported trials declared that sponsors had no role in the design and conduct of the studies; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscripts. References 1 Global Report on Diabetes . Geneva: World Health Organization; 2016 . http://www.who.int/diabetes/global-report/en/ (28 January 2018, date last accessed). 2 IDF Diabetes Atlas, 8th ed . International Diabetes Federation; 2017 . www.diabetesatlas.org (28 January 2018, date last accessed). 3 Sarwar N , Gao P , Seshasai SR , Gobin R , Kaptoge S , Di Angelantonio E et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies . Lancet 2010 ; 375 : 2215 – 22 . Google Scholar CrossRef Search ADS PubMed 4 Grundy SM , Benjamin IJ , Burke GL , Chait A , Eckel RH , Howard BV et al. Diabetes and cardiovascular disease: a statement for healthcare professionals from the American Heart Association . Circulation 1999 ; 100 : 1134 – 46 . Google Scholar CrossRef Search ADS PubMed 5 Upchurch CT , Barrett EJ. Clinical review: screening for coronary artery disease in type 2 diabetes . J Clin Endocrinol Metab 2012 ; 97 : 1434 – 42 . Google Scholar CrossRef Search ADS PubMed 6 American Diabetes Association . Standards of medical care in diabetes. Cardiovascular disease and risk management . Diabetes Care 2016 ; 39 Suppl 1 : S60 – 71 . PubMed 7 Jouven X , Lemaitre RN , Rea TD , Sotoodehnia N , Empana JP , Siscovick DS. Diabetes, glucose level, and risk of sudden cardiac death . Eur Heart J 2005 ; 26 : 2142 – 7 . Google Scholar CrossRef Search ADS PubMed 8 Zhang L , Li H , Zhang S , Jaacks LM , Li Y , Ji L. Silent myocardial ischemia detected by single photon emission computed tomography (SPECT) and risk of cardiac events among asymptomatic patients with type 2 diabetes: a meta-analysis of prospective studies . J Diabetes Complications 2014 ; 28 : 413 – 8 . Google Scholar CrossRef Search ADS PubMed 9 Haffner SM , Lehto S , Ronnemaa T , Pyorala K , Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction . N Engl J Med 1998 ; 339 : 229 – 34 . Google Scholar CrossRef Search ADS PubMed 10 Ryden L , Grant PJ , Anker SD , Berne C , Cosentino F , Danchin N et al. ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD . Eur Heart J 2013 ; 34 : 3035 – 87 . Google Scholar CrossRef Search ADS PubMed 11 Budoff MJ , Raggi P , Beller GA , Berman DS , Druz RS , Malik S et al. Noninvasive cardiovascular risk assessment of the asymptomatic diabetic patient: the imaging council of the American College of Cardiology . JACC Cardiovasc Imaging 2016 ; 9 : 176 – 92 . Google Scholar CrossRef Search ADS PubMed 12 Hachamovitch R , Hayes SW , Friedman JD , Cohen I , Berman DS. Comparison of the short-term survival benefit associated with revascularization compared with medical therapy in patients with no prior coronary artery disease undergoing stress myocardial perfusion single photon emission computed tomography . Circulation 2003 ; 107 : 2900 – 7 . Google Scholar CrossRef Search ADS PubMed 13 Min JK , Dunning A , Lin FY , Achenbach S , Al-Mallah M , Budoff MJ et al. Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the International Multicenter CONFIRM of 23, 854 patients without known coronary artery disease . J Am Coll Cardiol 2011 ; 58 : 849 – 60 . Google Scholar CrossRef Search ADS PubMed 14 Acampa W , Cantoni V , Green R , Maio F , Daniele S , Nappi C et al. Prognostic value of normal stress myocardial perfusion imaging in diabetic patients: a meta-analysis . J Nucl Cardiol 2014 ; 21 : 893 – 902 ; quiz: 890–2, 903–5. Google Scholar CrossRef Search ADS PubMed 15 Min JK , Labounty TM , Gomez MJ , Achenbach S , Al-Mallah M , Budoff MJ et al. Incremental prognostic value of coronary computed tomographic angiography over coronary artery calcium score for risk prediction of major adverse cardiac events in asymptomatic diabetic individuals . Atherosclerosis 2014 ; 232 : 298 – 304 . Google Scholar CrossRef Search ADS PubMed 16 Petretta M , Cuocolo A. Screening asymptomatic patients with type 2 diabetes is recommended: pro . J Nucl Cardiol 2015 ; 22 : 1225 – 8 . Google Scholar CrossRef Search ADS PubMed 17 Gibbons RJ. Screening asymptomatic patients with type 2 diabetes is recommended-Con . J Nucl Cardiol 2015 ; 22 : 1229 – 32 . Google Scholar CrossRef Search ADS PubMed 18 Acampa W , Petretta M , Evangelista L , Daniele S , Xhoxhi E , De Rimini ML et al. Myocardial perfusion imaging and risk classification for coronary heart disease in diabetic patients. The IDIS study: a prospective, multicentre trial . Eur J Nucl Med Mol Imaging 2012 ; 39 : 387 – 95 . Google Scholar CrossRef Search ADS PubMed 19 Zellweger MJ , Maraun M , Osterhues HH , Keller U , Muller-Brand J , Jeger R et al. Progression to overt or silent CAD in asymptomatic patients with diabetes mellitus at high coronary risk: main findings of the prospective multicenter BARDOT trial with a pilot randomized treatment substudy . JACC Cardiovasc Imaging 2014 ; 7 : 1001 – 10 . Google Scholar CrossRef Search ADS PubMed 20 Boden WE , O'Rourke RA , Teo KK , Hartigan PM , Maron DJ , Kostuk WJ et al. Optimal medical therapy with or without PCI for stable coronary disease . N Engl J Med 2007 ; 356 : 1503 – 16 . Google Scholar CrossRef Search ADS PubMed 21 Frye RL , August P , Brooks MM , Hardison RM , Kelsey SF , MacGregor JM et al. A randomized trial of therapies for type 2 diabetes and coronary artery disease . N Engl J Med 2009 ; 360 : 2503 – 15 . Google Scholar CrossRef Search ADS PubMed 22 Young LH , Wackers FJ , Chyun DA , Davey JA , Barrett EJ , Taillefer R et al. Cardiac outcomes after screening for asymptomatic coronary artery disease in patients with type 2 diabetes: the DIAD study: a randomized controlled trial . JAMA 2009 ; 301 : 1547 – 55 . Google Scholar CrossRef Search ADS PubMed 23 Muhlestein JB , Lappe DL , Lima JA , Rosen BD , May HT , Knight S et al. Effect of screening for coronary artery disease using CT angiography on mortality and cardiac events in high-risk patients with diabetes: the FACTOR-64 randomized clinical trial . JAMA 2014 ; 312 : 2234 – 43 . Google Scholar CrossRef Search ADS PubMed 24 Faglia E , Manuela M , Antonella Q , Michela G , Vincenzo C , Maurizio C et al. Risk reduction of cardiac events by screening of unknown asymptomatic coronary artery disease in subjects with type 2 diabetes mellitus at high cardiovascular risk: an open-label randomized pilot study . Am Heart J 2005 ; 149 : e1 – 6 . Google Scholar CrossRef Search ADS PubMed 25 Higgins JP , Altman DG , Gotzsche PC , Juni P , Moher D , Oxman AD et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials . BMJ 2011 ; 343 : d5928. Google Scholar CrossRef Search ADS PubMed 26 Egger M , Davey Smith G , Schneider M , Minder C. Bias in meta-analysis detected by a simple, graphical test . BMJ 1997 ; 315 : 629 – 34 . Google Scholar CrossRef Search ADS PubMed 27 Harbord RM , Egger M , Sterne JA. A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints . Stat Med 2006 ; 25 : 3443 – 57 . Google Scholar CrossRef Search ADS PubMed 28 Sterne JA , Sutton AJ , Ioannidis JP , Terrin N , Jones DR , Lau J et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials . BMJ 2011 ; 343 : d4002. Google Scholar CrossRef Search ADS PubMed 29 Atkins D , Best D , Briss PA , Eccles M , Falck-Ytter Y , Flottorp S et al. Grading quality of evidence and strength of recommendations . BMJ 2004 ; 328 : 1490. Google Scholar CrossRef Search ADS PubMed 30 Berkman ND , Lohr KN , Ansari MT , Balk EM , Kane R , McDonagh M et al. Grading the strength of a body of evidence when assessing health care interventions: an EPC update . J Clin Epidemiol 2015 ; 68 : 1312 – 24 . Google Scholar CrossRef Search ADS PubMed 31 Higgins JP , Thompson SG. Quantifying heterogeneity in a meta-analysis . Stat Med 2002 ; 21 : 1539 – 58 . Google Scholar CrossRef Search ADS PubMed 32 Cleophas TJ , Zwinderman AH. Meta-analysis . Circulation 2007 ; 115 : 2870 – 5 . Google Scholar CrossRef Search ADS PubMed 33 DerSimonian R , Laird N. Meta-analysis in clinical trials . Control Clin Trials 1986 ; 7 : 177 – 88 . Google Scholar CrossRef Search ADS PubMed 34 Moher D , Liberati A , Tetzlaff J , Altman DG , Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement . PLoS Med 2009 ; 6 : e1000097. Google Scholar CrossRef Search ADS PubMed 35 Lievre MM , Moulin P , Thivolet C , Rodier M , Rigalleau V , Penfornis A et al. Detection of silent myocardial ischemia in asymptomatic patients with diabetes: results of a randomized trial and meta-analysis assessing the effectiveness of systematic screening . Trials 2011 ; 12 : 23. Google Scholar CrossRef Search ADS PubMed 36 Turrini F , Scarlini S , Mannucci C , Messora R , Giovanardi P , Magnavacchi P et al. Does coronary Atherosclerosis Deserve to be Diagnosed earlY in Diabetic patients? The DADDY-D trial. Screening diabetic patients for unknown coronary disease . Eur J Intern Med 2015 ; 26 : 407 – 13 . Google Scholar CrossRef Search ADS PubMed 37 Gazzaruso C , Coppola A , Montalcini T , Valenti C , Pelissero G , Solerte SB et al. Screening for asymptomatic coronary artery disease can reduce cardiovascular mortality and morbidity in type 2 diabetic patients . Intern Emerg Med 2012 ; 7 : 257 – 66 . Google Scholar CrossRef Search ADS PubMed 38 Tsujimoto T , Sugiyama T , Yamamoto-Honda R , Kishimoto M , Noto H , Morooka M et al. Beneficial effects through aggressive coronary screening for type 2 diabetes patients with advanced vascular complications . Medicine (Baltimore) 2016 ; 95 : e4307. Google Scholar CrossRef Search ADS PubMed 39 Wolk MJ , Bailey SR , Doherty JU , Douglas PS , Hendel RC , Kramer CM et al. ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease . J Am Coll Cardiol 2014 ; 63 : 380 – 406 . Google Scholar CrossRef Search ADS PubMed 40 Montalescot G , Sechtem U , Achenbach S , Andreotti F , Arden C , Budaj A et al. 2013 ESC guidelines on the management of stable coronary artery disease . Eur Heart J 2013 ; 34 : 2949 – 3003 . Google Scholar CrossRef Search ADS PubMed 41 Greenland P , Alpert JS , Beller GA , Benjamin EJ , Budoff MJ , Fayad ZA et al. 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults . Circulation 2010 ; 122 : e584 – 636 . Google Scholar CrossRef Search ADS PubMed 42 Taylor F , Huffman MD , Macedo AF , Moore TH , Burke M , Davey Smith G et al. Statins for the primary prevention of cardiovascular disease . Cochrane Database Syst Rev 2013 ; 1 : CD004816 . 43 Min JK , Berman DS , Dunning A , Achenbach S , Al-Mallah M , Budoff MJ et al. All-cause mortality benefit of coronary revascularization vs. medical therapy in patients without known coronary artery disease undergoing coronary computed tomographic angiography: results from CONFIRM . Eur Heart J 2012 ; 33 : 3088 – 97 . Google Scholar CrossRef Search ADS PubMed Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Heart Journal – Cardiovascular Imaging Oxford University Press

Non-invasive screening for coronary artery disease in asymptomatic diabetic patients: a systematic review and meta-analysis of randomised controlled trials

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Oxford University Press
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.
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2047-2404
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10.1093/ehjci/jey014
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Abstract

Abstract It is unclear whether non-invasive screening of asymptomatic diabetic patients for coronary artery disease (CAD) may improve cardiac outcomes. Thus, we performed a systematic literature review and meta-analysis of randomised controlled trials (RCT’s) on this topic. We searched appropriate RCT’s in five online databases (PubMed/MEDLINE, Cochrane Library, Embase, Scopus, and Web of Science) from January 2000 to November 2017 and in 41 recent reviews. Two investigators independently extracted and assessed study data using standardised forms. Additional unpublished data were obtained from trial authors. The primary endpoint ‘any cardiac event’ was a composite of cardiac death, non-fatal myocardial infarction (MI), unstable angina (UA), or heart failure (HF) hospitalisation. We performed a meta-analysis of relative risks (RRs) with 95% confidence intervals (CI) using the Mantel–Haenszel method. We included five RCT’s with 3299 patients, of which 189 (5.7%) experienced any cardiac event on follow-up (weighted mean 4.1 years). Non-invasive CAD screening significantly reduced any cardiac event by 27% [RR 0.73 (95% CI 0.55–0.97), P = 0.028, number needed to screen 56]. This result was driven by important, albeit non-significant decreases in non-fatal MI [RR 0.65 (95% CI 0.41–1.02), P = 0.062] and HF hospitalisation [RR 0.61 (95% CI 0.33–1.10), P = 0.100]. Non-invasive CAD screening did not significantly affect cardiac death [RR 0.92 (95% CI 0.53–1.60), P = 0.77] and UA [RR 0.73 (95% CI 0.41–1.31), P = 0.29]. Compared with the standard care, non-invasive CAD screening reduced cardiac events by 27% in asymptomatic diabetic patients, largely through reductions in non-fatal MIs, and HF hospitalisations. The present results justify larger, appropriately powered trials to potentially revisit current recommendations. meta-analysis, screening, stress testing, cardiac imaging, coronary artery disease, diabetes mellitus Introduction Globally, an estimated 422 million people are living with diabetes mellitus, a number that has doubled over the past 20–30 years.1 By 2045, the International Diabetes Federation expects a further increase to 629 million diabetic patients worldwide.2 Diabetes mellitus confers a two-fold increased risk of coronary artery disease (CAD),3 which is the major cause of mortality and morbidity in diabetic patients.4–6 Unfortunately, in these patients, CAD may often be asymptomatic until the onset of myocardial infarction (MI) or sudden cardiac death.4,5,7 Indeed, silent cardiac ischaemia can be detected on average in 26% of asymptomatic diabetic patents, exposing them to a 3.5-fold increased risk of cardiac events.8 Hence, diabetes mellitus has been considered a CAD risk equivalent.9 The current standards of care for asymptomatic diabetic patients are based on risk factor modification, lifestyle changes, and medical therapy.6,10 However, the high cardiovascular risk in these patients has also generated substantial interest in the early detection of silent CAD by screening tests.5 In addition to exercise electrocardiogram test (EET), recent technological advances have produced a number of sophisticated imaging tools to assess non-invasively the presence and severity of CAD, including stress echocardiography (SE), stress radionuclide myocardial perfusion imaging (MPI), coronary artery calcium scoring (CACS), and computed tomography coronary angiography (CTCA).11 Myocardial ischaemia, high CACS and significant coronary stenosis have all been associated with worse outcomes in non-diabetic12,13 and diabetic patients.8,11,14,15 However, whether pre-emptive coronary revascularization and intensification of medical therapy based on routine CAD screening may improve outcomes of asymptomatic diabetic patients is currently under debate.16,17 Experts favouring screening5,16 refer to the improvement of risk classification,18 and the reduction of scintigraphic CAD progression with invasive treatment.19 However, opponents advocate optimal medical treatment without screening because revascularization has not convincingly been demonstrated to reduce cardiovascular events in diabetic patients.20,21 Moreover, first exploratory randomised controlled trials (RCT’s) failed to demonstrate any prognostic benefit of CAD screening. However, these trials may have suffered from under-sampling and potential statistical Type II error due to lower event rates than anticipated.22,23 We, therefore, sought to perform a systematic review and meta-analysis of published RCT’s to assess more precisely and with higher statistical power the potential reduction of cardiac events by a systematic non-invasive CAD screening strategy in asymptomatic patients with diabetes mellitus. Methods Literature search We performed a systematic search of medical articles published in peer-reviewed journals from January 2000 to November 2017 in English, German, or French in five online literature databases (PubMed/MEDLINE, Cochrane Library, Embase, Scopus, and Web of Science) using the following words in titles, abstracts, or keywords: (‘diabetes’ or ‘diabetic’), (‘asymptomatic’ or ‘occult’ or ‘silent’ or ‘subclinical’ or ‘unknown’), (‘coronary’ or ‘ischemia’ or ‘ischaemia’ or ‘CAD’), and (‘screening’ or ‘detection’ or ‘diagnosis’ or ‘identification’). Additionally, we manually searched the bibliographies of relevant reviews and guidelines of the last 10 years. Study selection We selected publications according to the following criteria: (i) prospective RCT’s published in peer-reviewed journals, (ii) patients with diabetes mellitus, without CAD symptoms or known CAD, (iii) randomisation to a non-invasive CAD screening strategy vs. standard care arm, and (iv) comparison of cardiac events after ≥1 year of follow-up, analysed with the intention-to-treat principle. Non-RCT’s with an adequate control group and meeting all other criteria were included in additional analyses. An overview of the search protocol is presented in Figure 1. Figure 1 View largeDownload slide Study flow diagram. Figure 1 View largeDownload slide Study flow diagram. Outcomes Our primary endpoint ‘any cardiac event’ was a composite of cardiac death, non-fatal MI, unstable angina (UA), or heart failure (HF) hospitalisation. Secondary endpoints were the individual components of the primary endpoint, all-cause death, coronary revascularization (regardless of percutaneous vs. surgical, as part of the screening protocol or not), and medication use. Data extraction Two investigators (O.F.C. and O.G.) independently extracted data regarding trial characteristics, potential bias, and pre-specified cardiac outcomes from the selected RCT’s using standardised forms designed for this study. Differences were solved by consensus. Composite outcome data were patient-based (i.e. one patient with several events counted as one positive case). For one study,24 we re-included one patient excluded for early non-cardiac death. Moreover, we contacted the authors of all selected trials to complete our outcome data. Thus, we were able to include unpublished results in our analyses. Study quality and risk of bias The study quality assessment comprised the risk of study bias, the publication bias, and the overall quality of evidence. The risk of study bias was assessed at the study and outcome level using the Cochrane Collaboration’s tool.25 Publication bias was evaluated using funnel plots26 and the Harbord–Egger test for asymmetry.27,28 Finally, overall quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method29 updated by the Evidence-based Practice Centre.30 Data synthesis and analysis Statistical analyses were conducted with Review Manager (RevMan) Version 5.3.5 (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). Additional graphics were generated with MedCalc version 17.4 (MedCalc Software bvba, Ostend, Belgium, 2017) and the Harbord–Egger test was performed with StatsDirect version 3.0.199 (StatsDirect Ltd., UK, 2013). Heterogeneity of trial results was tested using Cochrane’s Q and I2 statistic.31 We performed a meta-analysis of relative risks (RRs) with 95% confidence intervals (CIs) using the Mantel–Haenszel method and the fixed effect model.32 A random effects model33 was used if heterogeneity was significant (P ≤ 0.10 or I2 ≥ 50%)31 and in all additional analyses including non-RCT’s. The number needed to screen (NNS) was calculated for outcomes with significant results. All statistical tests were two-sided, and P-values <0.05 were considered as statistically significant, except <0.10 for heterogeneity analyses, as recommended.31 Sensitivity analyses For all primary and secondary endpoints, we sequentially excluded each trial from the meta-analysis to assess its specific effect on the pooled RR and significance. Additional analyses including non-randomised trials All primary and secondary endpoints were re-analysed after including data from the selected non-RCT’s. Regulatory aspects Because our study did not directly involve patients, but only outcome data from other studies, no approval from the local ethics committee was required. However, all selected trials reported about approval by an institutional review board and informed consent by each patient. Our analysis complied with the Declaration of Helsinki. We presented our results according to the PRISMA statement about systematic reviews and meta-analyses.34 This study did not receive any funding. Results Literature search Our literature search covered five online databases (5392 total records), and was completed using 35 reviews (1737 references) and six guidelines (1760 references), with substantial overlap of citations (Figure 1). We identified the five following appropriate RCT’s: the study by Faglia et al.,24 the ‘Detection of Ischaemia in Asymptomatic Diabetics’ (DIAD) study,22 the ‘Do You Need to Assess Myocardial Ischaemia in Type-2 diabetes’ (DYNAMIT) study,35 the FACTOR-64 study,23 and the ‘Does coronary Atherosclerosis Deserve to be Diagnosed earlY in Diabetic patients’ (DADDY-D) study.36 Study characteristics Table 1 presents important characteristics of the selected RCT’s. These trials included between 141 and 1123 patients, with a total of 3299 patients. Mean age ranged from 60.1 to 63.9 years, the proportion of male patients from 52% to 80% and mean follow-up duration from 3.5 to 4.8 years (weighted mean 4.1 years). Inclusion criteria were based on age and presence of diabetes, and three studies required additional cardiovascular risk factors. Screening was performed with EET, SE, MPI, CTCA with CACS, or a combination of them. The studies also vary in the type of clinical response with which pathological imaging findings were met: in DIAD, patients were treated according to the best judgment of the primary medical provider. In DYNAMIT, further investigations were left at the cardiologist’s decision. In Faglia et al.24 and DADDY-D, patients with positive tests were directly offered an invasive coronary angiography (ICA). FACTOR-64 provided protocol-based recommendations to the referring physicians on intensification of medical treatment and the use of ICA or further non-invasive testing based on the severity of findings. All selected RCT’s consistently found non-significant reductions of cardiac events in the screening arm, except Faglia et al.24 showing significant reductions of major and all cardiac events. Table 1 Overview of the randomised controlled trials included in the meta-analysis Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old CACS, coronary artery calcium score; CAD, coronary artery disease; CE, cardiac events (major CE = cardiac death or MI); CTCA, computed tomography coronary angiography; CV, cardiovascular; CVRF, cardiovascular risk factors; DM, diabetes mellitus; EET, exercise electrocardiogram test; ICA, invasive coronary angiography; MI, myocardial infarction; MPI, radionuclide myocardial perfusion imaging; SE, stress echocardiography. a In Faglia et al.,24 we re-included one patient excluded for early non-cardiac death. Table 1 Overview of the randomised controlled trials included in the meta-analysis Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old Study/author Faglia et al.24 DIAD22 DYNAMIT35 FACTOR-6423 DADDY-D36 Publication year 2005 2009 2011 2014 2015 Patients (n) 141 (+1)a 1123 615 899 520 Inclusion criteria Type 2 DM 45–76 years old ≥2 other CVRF Type 2 DM 50–75 years old Type 2 DM 50–75 years old ≥2 other CVRF Type 1 or 2 DM ♂ ≥50/♀ ≥55, DM for ≥3 years ♂ ≥40/♀ ≥45, DM for ≥5 years Type 2 DM 50–75 years old CV risk ≥10% Sinus rhythm Able to do EET Mean age (years) 60.1 60.8 63.9 61.5 61.9 Male gender (%) 55.6 53.5 54.5 52.2 80.0 Screening test EET and SE MPI EET or MPI CTCA and CACS EET Positive screening test 21.1% 5.9% moderate or large defects 21.5% positive or uncertain 11.9% moderate 10.7% severe 7.6% Treatment strategy ICA and cardiac follow-up if any test was positive At the referring physician’s discretion According to the cardiologist’s decision Recommendation based on stenosis severity and CACS ICA if EET positive ICA performed after positive test (%) 93.3 15.2 55.9 47.3 85.0 Mean follow-up (years) 4.5 4.8 3.5 4.0 3.6 Annual rate of major CE (%) 1.9 0.6 1.0 0.8 1.4 Main results of screening Significant ↘ of major and all CE Non-significant ↘ of major CE Non-significant ↘ of MI, no effect on combined CE Non-significant ↘ of combined CE Non-significant ↘ of major CE, but significant ↘ in >60 years old CACS, coronary artery calcium score; CAD, coronary artery disease; CE, cardiac events (major CE = cardiac death or MI); CTCA, computed tomography coronary angiography; CV, cardiovascular; CVRF, cardiovascular risk factors; DM, diabetes mellitus; EET, exercise electrocardiogram test; ICA, invasive coronary angiography; MI, myocardial infarction; MPI, radionuclide myocardial perfusion imaging; SE, stress echocardiography. a In Faglia et al.,24 we re-included one patient excluded for early non-cardiac death. Study quality and risk of bias The five RCT’s had a globally low risk of study bias when assessed with the Cochrane tool (see Supplementary data online, Figure S1). Importantly, all of them seemed non-blinded to patients and physicians regarding trial arm. However, knowledge of screening status and screening results was an integral part of the interventions and thus, we did not consider it as a bias. Two studies had a comparable number of patients lost to follow-up and of patients experiencing cardiac events, leading to a potential minor attrition bias. Trial results were direct, as they were based on clinical outcomes. Consistency of results was good for most of these outcomes. Regarding publication bias, funnel plots showed a somewhat outlying position for Faglia et al.,24 consistent with its small size and more positive results (see Supplementary data online, Figure S2). However, we found no significant asymmetry with the Harbord–Egger test (P = 0.123 for the main composite outcome). Finally, the individual trials lacked precision, due to broad CIs, but performing a meta-analysis produced more precise results. However, these analyses are limited in the presence of five RCT’s. Thus, we rated the strength of evidence as moderate, according to the updated GRADE method. Primary outcome and its components In our sample of five RCT’s, a total of 3299 patients were randomised to a screening arm (n = 1652) or a control arm (n = 1647). A total of 189 (5.7%) patients experienced cardiac events. A strategy of non-invasive CAD screening significantly reduced any cardiac event by 27% [RR 0.73 (95% CI 0.55–0.97), P = 0.028, I2 = 36%, NNS = 56, Figure 2]. This was largely driven by a decrease in non-fatal MI [RR 0.65 (95% CI 0.41–1.02), P = 0.062, I2 = 0%] and HF hospitalisation [RR 0.61 (95% CI 0.33–1.10), P = 0.100, I2 = 29%], although both findings fell short of statistical significance when assessed separately (Figure 3). Screening tended to reduce UA [RR 0.73 (95% CI 0.41–1.31), P = 0.29, I2 = 0%], but had no relevant effect on cardiac death [RR 0.92 (95% CI 0.53–1.60), P = 0.77, I2 = 39%, Figure 3]. Figure 2 View largeDownload slide Meta-analysis of the primary endpoint: any cardiac event. Any cardiac event is a composite of cardiac death, non-fatal myocardial infarction, unstable angina, or heart failure hospitalisation. Figure 2 View largeDownload slide Meta-analysis of the primary endpoint: any cardiac event. Any cardiac event is a composite of cardiac death, non-fatal myocardial infarction, unstable angina, or heart failure hospitalisation. Figure 3 View largeDownload slide Meta-analysis of components of the primary endpoint. Figure 3 View largeDownload slide Meta-analysis of components of the primary endpoint. Secondary outcomes All-cause death was not affected by screening [RR 0.92 (95% CI 0.65–1.30), P = 0.63, I2 = 0%, Figure 4]. Coronary revascularization was heterogeneous across the RCT’s (I2 = 79%). Whereas trials with functional testing (EET and MPI) tended to decrease revascularization rates, anatomical testing (CTCA + CACS in FACTOR-64) significantly increased it (Figure 4). Analyses of medication use showed no significant effect of screening, but detected a trend towards increased statin use [RR 1.05 (95% CI 0.99–1.10), P = 0.092, I2 = 31%, see Supplementary data online, Figure S3]. Figure 4 View largeDownload slide Meta-analysis of secondary endpoints. Figure 4 View largeDownload slide Meta-analysis of secondary endpoints. Sensitivity analysis In the primary endpoint analysis, excluding Faglia et al.24 or DADDY-D numerically increased the pooled RR, whereas excluding DIAD, DYNAMIT, or FACTOR-64 reduced it. Excluding Faglia et al. or DADDY-D made the pooled RR statistically non-significant, whereas excluding DIAD made it more significant. The most divergent results were: without Faglia et al. [RR 0.82 (95% CI 0.61–1.09), P = 0.172, I2 = 0%], without DIAD [RR 0.65 (95% CI 0.47–0.91), P = 0.013, I2 = 41%, NNS = 38]. Among secondary outcomes, screening would tend to reduce cardiac death without DYNAMIT [RR 0.70 (95% CI 0.37–1.30), P = 0.26, I2 = 16%] and to reduce coronary revascularizations without FACTOR-64 [RR 0.81 (95% CI 0.59–1.09), P = 0.159, I2 = 0%]. Additional analyses including non-randomised trials In the literature search, we found two relevant non-RCT’s with appropriate control groups, both showing reductions in cardiovascular events in screened asymptomatic patients with diabetes: one by Gazzaruso et al.37 using EET ± SE or MPI and one by Tsujimoto et al.38 using MPI. Including these non-RCT’s into the primary outcome analysis resulted in a stronger reduction of any cardiac event by 42% [RR 0.58 (95% CI 0.37–0.91), P = 0.017, I2 = 66%, NNS = 35, Figure 5], driven by a significant reduction of non-fatal MI [RR 0.52 (95% CI 0.32–0.84), P = 0.008, I2 = 31%]. Secondary endpoints including non-RCT’s are presented in Supplementary data online, Figure S4. Figure 5 View largeDownload slide Meta-analysis of any cardiac event in randomised controlled trials and non-randomised trials. Figure 5 View largeDownload slide Meta-analysis of any cardiac event in randomised controlled trials and non-randomised trials. Discussion The present meta-analysis of five RCT’s including 3299 asymptomatic diabetic patients compared a strategy of routine CAD screening vs. standard of care with regard to cardiac outcomes over a weighted mean follow-up of 4.1 years. We found a significant reduction in the primary composite endpoint of any cardiac event by 27%. This endpoint reduction was mainly driven by lower rates of non-fatal MI (−35%) and HF hospitalisations (−39%), although both findings fell short of statistical significance when assessed separately. Fifty-six asymptomatic Type 2 diabetics would have to undergo CAD screening to prevent one cardiac event over a 4-year follow-up. Overall quality of evidence was high. Including data from two non-randomised trials in the meta-analysis further strengthened the effect of screening on the primary endpoint (−42%) and even showed a significant reduction in non-fatal MI by 48% in favour of screening. This primary outcome reduction was fairly homogenous over the five trials included in the meta-analysis, but fell short of statistical significance when assessed separately in each individual trial (except in the small trial by Faglia et al.24). This may be explained by a Type II statistical error, in which the null hypothesis fails to be rejected due to systematic under-sampling, caused by the unexpected low cardiac event rates in all trials. Indeed, in DIAD and FACTOR-64, the two largest RCT’s included in this meta-analysis, the average annual major cardiac event rate (cardiac death or MI) was 0.6%, and 0.8%, respectively, i.e. 3–4 times lower than anticipated.22,23 Unlike the other RCT’s, all of which had higher event rates, DIAD and FACTOR-64 did not require additional risk factors as inclusion criteria. Hence, it is likely that both trials were underpowered to detect small differences in risk at a reasonable power (80–90%). Most of the studies encountered difficulties in enrolling patients: DYNAMIT was stopped early due to low patient recruitment rates,35 whereas FACTOR-64 and DADDY-D compensated low recruitment rates by extending the follow-up duration.23,36 The present meta-analysis overcomes the statistical limitations of the individual trials to some extent and confirms the small but significant tendency towards improved outcomes with the use of a CAD screening strategy. Notably, pathological screening results were treated differently across the different trials. In DIAD and DYNAMIT, specific treatment decisions regarding intensification of medical treatment and/or referral to ICA were left at the discretion of the treating physician or the study cardiologist.22,35 In Faglia et al.24 and DADDY-D,36 patients with pathological test results were directly offered an ICA. Only FACTOR-64 provided standardised protocol-based recommendations for treatment escalation in the screening arm: these included lower-than-standard goals for cholesterol, HbA1c, and blood pressure. Patients with severe or moderate coronary stenoses on CTCA were sent for ICA or further non-invasive testing, respectively. However, despite more aggressive treatment in 70% of patients in the screening arm of FACTOR-64, differences in lipid levels, blood pressure, and HbA1c between both groups were very modest after treatment. Coronary angiography and revascularization rates were slightly higher in the screening arm compared with the standard-of-care arm. Possibly as a result of this, a small non-significant trend towards improved outcomes was observed in the screening arm.23 In DIAD, there were no significant differences with regard to medical treatment and the rate of revascularization between both groups. In fact, only 15% of patients with moderate to large perfusion defects underwent ICA, and numerically more patients with normal imaging findings than patients with perfusion defects were revascularized. Almost 80% of patients with moderate to large perfusion defects, and 96% of patients with small perfusion defects were denied a revascularization procedure. Thus, presumably those patients with the largest expected benefit from revascularization were withheld.12 These discrepancies between individual and recommended treatment decisions may account to some extent for the lack of benefit in the screening arm of DIAD.22 In DYNAMIT and DADDY-D, drug usage and revascularization rates were similar among both groups, but severity of ischaemia and respective revascularization rates are not reported.35,36 Current recommendations for CAD screening in asymptomatic diabetic patients are rather restrictive, based on the negative results of the aforementioned screening trials. Multimodality appropriate use criteria for CAD detection consider EET as ‘appropriate’ and imaging tests as ‘maybe appropriate’ in asymptomatic diabetic patients.39 European and American cardiological societies do not recommend systematic screening of asymptomatic diabetic patients, but consider CACS as reasonable and mention that stress imaging may be considered.40,41 However, the American Diabetes Association clearly discourages routine CAD screening on the following grounds6: on one hand, diabetic patients should already be on aggressive primary prevention therapies regardless of the presence or absence of significant CAD, on the other hand, large randomised trials did not report any global advantage of revascularization over medical therapy in unselected Type 2 diabetic patients with stable CAD.20,21 The present meta-analysis argues against current recommendations and encourages further research into screening strategies for asymptomatic diabetic patients. Given the large global prevalence of diabetes mellitus and the considerable costs of current non-invasive CAD imaging tests, it would be premature to recommend routine CAD screening for every asymptomatic diabetic patient. Moreover, the present meta-analysis did not demonstrate any mortality benefit with a screening strategy. However, the benefit of a screening strategy in this study can be compared with the effect of statin use for primary prevention of coronary heart disease events (−27%, number needed to treat 78).42 Further large and appropriately powered trials are required to allow a more precise analysis of the magnitude of benefit and to assess pre-specified subgroups in which screening strategies may offer larger benefits. Then, cost-effectiveness studies should assess the financial impact and economic benefits of a CAD screening programme in diabetic patients. Limitations This meta-analysis was based on a variety of screening modalities: FACTOR-64 used CACS and CTCA,23 while DIAD was conducted with MPI,22 DYNAMIT and DADDY-D relied on EET,35,36 whereas Faglia et al.24 combined EET and SE. These methodological differences may be perceived as a limitation of our meta-analysis. However, with the exception of EET, all CAD imaging tests have demonstrated uniformly a very high sensitivity and specificity for detecting CAD.40 Moreover, all non-invasive tests predict cardiac events based on the severity of their findings, also in patients with diabetes.8,11,14,15 Furthermore, the extent of disease has been shown to interact with the treatment strategy with regard to cardiac outcomes. Thus, patients with more severe or extensive CAD on non-invasive testing have better outcomes with revascularization, while in patients with lower CAD severity, medical therapy appears equivalent.12,43 The design of this study-level meta-analysis precludes assessing specific subgroups for their respective benefits of screening strategies. Given the small prognostic benefit of a routine screening strategy, it may well be that larger benefits are observed in specific subgroups, such as the very high-risk diabetic patients (e.g. those in which medical therapy fails to reach therapeutic goals or with multiple risk factors), the elder diabetics (as suggested in DADDY-D36), or those with a high level of physical activity. Moreover, only FACTOR-64 included 12% of patients with Type 1 diabetes.23 This corresponds to 3% of our pooled sample, with 97% of patients having Type 2 diabetes. Thus, our results essentially apply to Type 2 diabetes. However, our meta-analysis also has strengths, such as the low risk of bias of the selected RCT’s, the overall quality of evidence, the detailed outcome assessment, the addition of unpublished data, and the additional analyses with non-randomised trials. Conclusion The present systematic review and meta-analysis suggests a reduction of cardiac events with the use of a CAD screening strategy in asymptomatic diabetic patients. These results should encourage further research into this issue by design of larger, appropriately sized randomised trials to address the exact magnitude of the effect in specific subgroups. Acknowledgements We thank the trial authors for providing additional information and unpublished data: Dr C. Gazzaruso, Prof M. Noda, Dr T. Tsujimoto, Dr F. Turrini, Dr M. Lièvre, Dr J.B. Muhlestein, and Dr S. Knight. Supplementary data Supplementary data are available at European Heart Journal - Cardiovascular Imaging online. Conflict of interest: None declared for this study. In the original trials, Faglia et al. did not report about conflicts of interests or financial support. DIAD was supported by Bristol Myers-Squibb Medical Imaging and Astellas Pharma, which provided technetium-99m-sestamibi and adenosine. DYNAMIT was supported by the French Social Security, ALFEDIAM, Aventis, Pfizer-Parke-Davis, and Servier. FACTOR-64 was supported by Toshiba Corporation and Bracco Corporation. DADDY-D reported no conflict of interest and no private funding, but additional study materials from Azienda USL di Modena. Gazzaruso et al. reported no conflict of interest. Tsujimoto et al. were supported by the Japan Diabetes Foundation, and reported speaker honoraria and grants for the last author. 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All-cause mortality benefit of coronary revascularization vs. medical therapy in patients without known coronary artery disease undergoing coronary computed tomographic angiography: results from CONFIRM . Eur Heart J 2012 ; 33 : 3088 – 97 . Google Scholar CrossRef Search ADS PubMed Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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European Heart Journal – Cardiovascular ImagingOxford University Press

Published: Feb 14, 2018

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